129 results about "Integral sliding mode" patented technology

The invention relates to a mechanical arm trajectory tracking method based on improved integral terminal sliding mode control, and belongs to the technical field of robot control. According to the method, an integral sliding mode surface and a fast terminal sliding mode surface are combined to create a non-singular fast integral terminal sliding mode surface; an improved index reaching law is designed, and the buffeting problem existing in sliding mode control is weakened. The method comprises the following steps: S1, based on physical parameters of the mechanical arm, establishing a mechanical arm dynamic model by adopting a DH parameter method and a Lagrange dynamics principle; s2, constructing a non-singular fast integral terminal sliding mode surface for the dynamic system; s3, designing an improved reaching law fused with a hyperbolic tangent function; s4, performing trajectory planning by using a Cartesian space interpolation algorithm; s5, integrating the sliding mode surface, the improved reaching law and the dynamical model to derive a trajectory tracking control law; s6, constructing a closed-loop control model of the improved integral terminal sliding mode controller and the mechanical arm system; and S7, the control parameters are adjusted, and mechanical arm trajectory tracking is conducted. The control method serves as a controller to conduct trajectory tracking application on the six-degree-of-freedom mechanical arm. The result shows that on the premise of ensuring finite time convergence, the control method effectively eliminates the buffeting phenomenon of traditional sliding mode control, improves the trajectory tracking precision, has high robustness to external disturbance, and can realize high-precision tracking control of a mechanical arm end effector on a complex trajectory.

The invention discloses a three-level inverter dual-tracking model prediction control method and an inverter, and the method comprises the steps: constructing an integral sliding mode observer, and obtaining a current prediction value and a lumped disturbance estimation value through the integral sliding mode observer; calculating a voltage error of the inverter, and substituting the voltage error into the PI controller to obtain a voltage tracking control item; based on the voltage tracking control term, a switching state that minimizes the cost function is selected to control the inverter. The integral sliding mode observer is configured to calculate a current prediction error between a current prediction value of a current control period and a system output current, introduce an integrator to track the current prediction error, and generate an error function based on an output result of the integrator and the current prediction error. And feeding back a current predicted value and a lumped disturbance estimated value of the next control period through an error function. According to the invention, the method can achieve the quick estimation of the operation state of the inverter and the robust compensation of disturbance, reduces the steady-state tracking error, and reduces the total harmonic distortion of the inverter.

The invention discloses an unmanned ship formation keeping control method under communication time delay, and belongs to the technical field of intelligent ship navigation control, and the method comprises the steps: building an unmanned ship motion model based on a built unmanned ship three-degree-of-freedom motion model, a state-space equation of the unmanned ship three-degree-of-freedom motion model, and an environment disturbance mathematical model; aiming at the problems of wind wave flow disturbance and communication time delay suffered by the unmanned ship formation, constructing a superhelix integral sliding mode observer and a self-adaptive time delay estimator; a formation control system is built by combining a fixed time theory, a formation controller of a nonsingular terminal sliding mode and a superhelix integral sliding mode observer, and formation keeping of the unmanned surface vehicle is achieved; and finally verifying through a simulation experiment. The formation control system is built based on the fixed time theory and the nonsingular terminal sliding mode control method for the unmanned surface vehicle formation, the unmanned surface vehicle formation control precision is effectively improved, unmanned surface vehicle formation shape keeping control under composite disturbance is achieved, and the method has great significance in promoting precise development of unmanned surface vehicle formation operation.

The invention relates to the technical field of motor control, in particular to a control and parameter intelligent optimization method for an anti-impact high-precision PMSM (permanent magnet synchronous motor) feeding servo system, which comprises the following steps of: S1, establishing a physical structure and a dynamic model of a PMSM driving feeding system; s2, designing a variable gain fractional order super-spiral sliding mode controller VGFSTSMC, realizing finite time convergence of position tracking errors by dynamically adjusting and controlling gain coefficients, and inhibiting system jitter; s3, designing an adaptive sliding mode disturbance observer ASMDO, and estimating and compensating unknown disturbance in real time through adaptive gain adjustment and an integral sliding mode surface; s4, identifying a system Stribeck friction model based on a least square method, and inputting the system Stribeck friction model as a friction feedforward compensation FFC to a current loop to reduce the disturbance uncertainty of the system; s5, dynamically adjusting and optimizing control parameters of the VGFSTSMC and the ASMDO by adopting an optimization algorithm so as to minimize a root-mean-square value RMSE of a position tracking error and a maximum instantaneous error; and S6, VGFSTSMC, ASMDO and FFC are combined with an optimization algorithm, and the PMSM is driven to realize high-precision position control.

The invention relates to the technical field of mining permanent magnet synchronous motor sensorless control, and particularly discloses a composite sliding mode control and adaptive phase-locked loop collaborative optimization method. Aiming at the technical bottlenecks of a traditional control strategy in the aspects of rotating speed fluctuation suppression, load disturbance compensation and rotor position observation precision, a collaborative architecture of a time-varying integral terminal sliding mode control module, a sliding mode disturbance observation module and a self-adaptive phase-locked loop module is constructed, so that the dynamic performance optimization of the system is realized. According to the method, through the dynamic coupling design of the time-varying gain nonlinear reaching law and the fast integral terminal sliding mode surface, the convergence speed and the buffeting suppression requirement are balanced while the disturbance dynamic influence is eliminated; multi-dimensional decoupling observation of external load disturbance is realized based on a hierarchical disturbance observer architecture, and a disturbance real-time suppression path is established in combination with a feed-forward compensation strategy; and constructing an error self-adaptive correction mechanism of rotor position observation by dynamically adjusting a phase-locked loop proportionality coefficient and a phase compensation parameter. The limitation of parameter solidification and observation coupling in traditional control is broken through, the rotating speed tracking stability, the position observation precision and the anti-interference capability under complex working conditions are remarkably improved, and an innovative solution is provided for a high-precision servo driving system.

A motor control method based on an improved composite reaching law and a sliding mode observer belongs to the technical field of permanent magnet synchronous motor system control, and comprises the following steps: firstly, considering motor internal parameter change and external load disturbance, and establishing a disturbance-containing permanent magnet synchronous motor mathematical model and a motor state equation; secondly, providing a new switching function, constructing an improved composite reaching law, completing stability proving, and analyzing rapid convergence and buffeting suppression capability of the improved composite reaching law; then constructing an anti-saturation integral sliding mode surface, and designing a sliding mode speed controller according to the permanent magnet synchronous motor mathematical model containing disturbance, the anti-saturation integral sliding mode surface and the improved composite reaching law; and finally, aiming at disturbance in the controller, designing an improved sliding mode disturbance observer, and completing stability proving. The contradiction between fast convergence and buffeting suppression in an existing sliding mode reaching law scheme is solved, and the provided improved sliding mode observer improves the observation precision and the response speed.

According to the continuous self-adaptive integral sliding mode leader-following multi-robot affine formation control method based on the event triggering mechanism, distributed control and affine formation strategies are fused, a formation controller with high maneuverability and high robustness is constructed, the event triggering mechanism is introduced to reduce the communication load and the control frequency, and the control efficiency is improved. The method belongs to the technical field of multi-robot intelligent cooperative control. Aiming at the common problem of insufficient formation rigidity and flexibility in a multi-robot formation control task, the invention provides a cooperative control method capable of realizing various affine transformations such as zooming, rotating, shearing, coplanar and collinear, and the cooperative control method has good environmental adaptability and system performance.

The invention provides a finite time cooperative tracking control method based on an adaptive RBF neural network, and belongs to the technical field of networked multi-agent control strategies. Constructing a dynamic mathematical model of a high-order all-drive uncertain nonlinear multi-agent system comprising a virtual leader and a follower; according to a cooperative tracking control target and uncertain items in the system, constructing an error dynamic system comprising an adaptive RBF neural network estimation compensation item; designing a finite time integral sliding mode surface based on a high-order all-drive system theory; designing linearization parameters of a finite time integral sliding mode surface based on a pole assignment method according to system dynamic performance and finite time convergence requirements, and obtaining a finite time integral sliding mode controller; and designing a self-adaptive updating law of an upper bound of an RBF neural network weight and an approximate error, and substituting the network weight and the approximate error into a finite time integral sliding mode controller to realize cooperative tracking control of finite time.

The invention provides an FTESO-based parallel inverter system recursive nonsingular terminal sliding mode control method, and the method comprises the following steps: firstly, designing FTESO to estimate system load disturbance; and secondly, designing an RNTSM control law for the inverter system based on FTESO compensation, so that the inverter system can completely overcome the influence of load interference, and the robustness of filtering parameter perturbation is enhanced. According to the method, the recursive terminal sliding mode surface formed by combining the non-singular fast terminal sliding mode and the integral sliding mode is adopted, it can be ensured that the output voltage of an inverter system rapidly tracks the reference voltage of the inverter system within finite time, and system buffeting is effectively weakened.

The invention discloses a permanent magnet synchronous motor control method of an adaptive fractional order fast terminal sliding mode. The method comprises the following steps: firstly, constructing a mathematical model of the permanent magnet synchronous motor in a d-q axis rotor rotating coordinate system; then designing a fractional order fast terminal sliding mode surface, and solving an equivalent control law of sliding mode control based on the designed fractional order fast terminal sliding mode surface; performing adaptive design on the switching control gain and the boundary layer thickness to obtain an adaptive switching control law; and integrating the equivalent control law and the adaptive switching control law to obtain a total control law. Compared with existing surface-mounted permanent magnet synchronous motor sliding mode control, the surface-mounted permanent magnet synchronous motor sliding mode control method introduces a fractional order fast terminal sliding mode surface on the basis of a traditional integral sliding mode so as to reduce system buffeting and ensure that tracking errors converge in finite time, and meanwhile designs a self-adaptive control law of switching control rate gain and boundary layer thickness. The uncertainty influence of external disturbance is counteracted, and the robustness of the system is improved.

The invention discloses a self-adaptive cooperative control strategy based on a variable speed reaching law and a neural network, belongs to the field of intelligent control, and mainly aims at estimating and compensating uncertainty, external disturbance and actuator saturation existing in a queue in queue control and improving the stability, robustness and control performance of the whole queue. The method comprises the following steps: establishing a queue system model with uncertainty, external disturbance and actuator saturation; establishing a Gaussian error function approximation strategy; establishing a tracking error; establishing a variable speed reaching law; establishing a queue integral sliding mode error; establishing a queue coupling sliding mode error; establishing an adaptive parameter estimation mechanism for external disturbance and Gaussian function approximation errors in the queue; establishing a neural network estimation mechanism for uncertainty in the queue; and establishing a queue integral sliding mode control strategy based on a variable speed reaching law, a Gaussian error function approximation strategy, an adaptive parameter estimation mechanism and a neural network estimation mechanism. The method is used for queue cooperative intelligent control.

The invention relates to the technical field of closed-loop drift control, and particularly discloses a closed-loop drift control method and system for an autonomous vehicle in an uncertain environment, and the method comprises the steps: building a vehicle kinematic model based on a Frenet coordinate system, and constructing an MPC path tracking controller with a preview mechanism; establishing a three-degree-of-freedom vehicle dynamics model with additional yawing moment; the method comprises the following steps: establishing a UniTile-Ctrl tire dynamic model; designing a robust drift controller by combining LQR and integral sliding mode control on the basis of the whole vehicle dynamic model and the tire dynamic model, designing a torque distribution module by taking minimization of distribution error and tire load utilization rate as targets on the basis of ideal rear wheel rotating speed and additional yawing moment output by the robust controller, and outputting a torque distribution model; according to the drifting vehicle tracking control method, closed-loop drifting control can be achieved, the drifting vehicle tracking control performance and robustness are improved, and safety guarantee is provided for limit control over the uncertain road surface of the vehicle.

The invention discloses a permanent magnet synchronous motor control method based on self-tuning prediction and a neural network, which aims at the inductance parameter mismatch problem in incremental dead-beat prediction control, adopts an inductance mismatch diagnosis and self-tuning mechanism to dynamically adjust model parameters and weight coefficients, and improves the robustness and dynamic response performance of a current loop. A neural network sliding mode control method is introduced into a speed ring, adaptive compensation of nonlinear disturbance and parameter uncertainty is realized by constructing an integral sliding mode surface and adjusting a sliding mode gain on line, and a stable and reliable current control instruction is output; meanwhile, the observer part constructs an improved super-spiral sliding-mode observer, the electrical angle and d-q axis composite disturbance can be estimated in real time with high precision, effective compensation information is provided for current control, and the overall stability and robustness of the system are further enhanced.

The invention discloses a multi-agent sliding mode safety control method based on dynamic event triggering under hybrid network attack, and the control method comprises the following steps: building a multi-agent system model comprising spoofing attack and DoS attack; in order to cope with hybrid network attacks, an integral sliding mode surface function is constructed, an online estimation method is provided, and an unknown network attack mode can be estimated in real time in the absence of prior information; a novel self-adaptive sliding mode controller is developed, and the accessibility of a preset sliding mode surface is ensured; by introducing an auxiliary variable, a dynamic and static event triggering mechanism in the framework is considered, so that the use of communication resources is minimized; a Lyapunov stability theory and a finite time method are utilized to analyze the convergence of the multi-agent system under the control strategy. According to the control method provided by the invention, the influence of spoofing attack and DoS attack on the system can be eliminated, so that the state of the multi-agent system is consistent within finite time.

The invention discloses a flexible joint mechanical arm AISMC compensation control method under singular perturbation decomposition, and belongs to the field of flexible joint mechanical arm control, and the method comprises the following steps: S1, building a flexible joint mechanical arm dynamic model containing uncertain composite disturbance, and decoupling the model into a slow variable subsystem and a fast variable subsystem; s2, estimating lumped matching disturbance in the slow varying subsystem by using a compensation function observer; s3, constructing an integral sliding mode surface and a self-adaptive reaching law with dead zone correction for the slow-varying subsystem; designing a linear quadratic regulator for the quick-change subsystem, defining a performance index, and solving a Riccati equation to obtain an optimal control law; s4, superposing the slow-varying subsystem control law and the fast-varying subsystem control law to obtain integral control input; and S5, performing simulation verification. By adopting the flexible joint mechanical arm AISMC compensation control method under singular perturbation decomposition, trajectory tracking precision, robustness and stability are considered, and the method has a wide application prospect.

The invention belongs to the technical field of robot control, and discloses a visual servo intelligent robust control method for a mobile mechanical arm for a complex operation task, which comprises the following steps of: 1, acquiring a working scene image, and calculating a space coordinate of a target feature point in real time through a projection transformation model; step 2, dynamically inhibiting visual measurement noise by adopting adaptive Kalman filtering, generating a feedforward compensation signal through an integral sliding mode observer, and decoupling chassis slippage disturbance; step 3, inputting the pose signal into a radial RBF neural network, designing an RBF gain scheduler, and adjusting an output proportion-integral gain in real time to suppress external time-varying disturbance; 4, adopting a hybrid visual servo mode switching mechanism, and generating a mobile platform control instruction through an integral sliding mode surface in a position servo mode; and 5, designing a three-order composite controller to drive the mechanical arm so as to realize accurate grabbing. According to the method, the grabbing deviation caused by kinematics uncertainty of the mobile platform and dynamic environment disturbance is eliminated.

The invention discloses a permanent magnet synchronous motor model-free quasi-resonance sliding mode control method and system. The method comprises the following steps: S1, establishing a model-free quasi-resonant sliding mode current controller which is configured with an input and output hyper-local model based on motor control and is a function of a primary time derivative of an output variable relative to a control variable and unknown disturbance; setting an integral sliding mode surface with a quasi-resonance term, and obtaining a control law of the control variable in combination with the hyper-local model; s2, setting an extended state observer which is connected with the model-free quasi-resonance sliding mode current controller and is used for observing the unknown disturbance controlled by the motor and applying the unknown disturbance to a control law of the control variable; and S3, obtaining an observation value of an output variable, and obtaining a value of a control variable applied to motor control according to the control law of the control variable. The model-free quasi-resonance sliding mode control system comprises the model-free quasi-resonance sliding mode current controller and an expansion state observer. The speed fluctuation is reduced, and the torque output quality is improved.

The invention discloses a TBM cutterhead main drive intelligent decision-making method and system, and belongs to the technical field of cutterhead drive control. Unified regulation and control and target torque distribution of a driving system are realized by constructing a master-slave type multi-driving-unit collaborative architecture; a fault is identified by monitoring a current signal, a voltage vector is reconstructed according to the fault type, and continuous and stable output under the fault is ensured; a disturbance observation method based on an integral sliding mode is provided, and control deviation caused by system disturbance and parameter changes is dynamically estimated and compensated; an MPTA control strategy of high-frequency virtual signal injection is designed, and utilization of reluctance torque and stable tracking of an MTPA working point are achieved; the torque output capacity of a fault unit and the torque margin of a healthy unit are comprehensively considered, a load distribution strategy is planned, and the overall loading capacity and the operation life of the driving system are improved.

The invention discloses a multi-vector model predictive control method for a dual three-phase permanent magnet synchronous generator considering a harmonic space, which comprises the following steps: selecting three voltage vectors to construct a target voltage vector in each control sector, substituting the target voltage vector into a discrete predictive control model to obtain a predictive current at the next moment, and further constructing a value function to obtain a predictive current at the next moment; and selecting an optimal virtual voltage vector set of the two subspaces and action time of the optimal virtual voltage vector through a minimum value function, combining control of the two subspaces into a control period, recalculating a switching sequence PWM signal, and acting on the rectifier. In the process of selecting the optimal virtual voltage vector set of the two subspaces, a superhelix integral sliding mode observer is used for observing current disturbance, and a composite controller is used for conducting zero static error tracking on harmonic waves in the z1z2 subspace. Under the condition that the dynamic performance is not affected, the fundamental wave space control performance is improved, the harmonic current is suppressed, and the steady-state performance of the DTP-PMSG is improved.

The invention relates to the technical field of motor driving, and discloses a brushless motor non-inductive FOC driving method and device, and the method comprises the steps: collecting a first three-phase stator current and a bus voltage of a brushless motor, and calculating a rotor position estimation value; performing coordinate transformation on the first three-phase stator current to obtain a first d-axis actual current and a first q-axis actual current, and calculating a first d-axis current error and a first q-axis current error; calculating a d-axis first-order integral value, a d-axis double-integral accumulated value, a q-axis first-order integral value and a q-axis double-integral accumulated value, and constructing a d-axis double-integral sliding mode surface and a q-axis double-integral sliding mode surface; according to the method, a d-axis compensation voltage instruction is generated based on the d-axis double-integral sliding mode surface, a q-axis compensation voltage instruction is generated based on the q-axis double-integral sliding mode surface, the d-axis compensation voltage instruction and the q-axis compensation voltage instruction are applied to the brushless motor, the problem of magnetic field orientation deviation caused by position estimation lag in non-inductive FOC driving is solved, and the output efficiency of the motor is improved.

The invention discloses a fixed time inclusion control method and system for a second-order nonlinear multi-agent system, and the method comprises the steps: defining a state tracking error according to a control target, augmenting the state tracking error into a matrix form, and designing an integral sliding mode surface for suppressing disturbance; designing a distributed fixed time inclusion consistency protocol and a dynamic event triggering mechanism based on position information and speed information according to the integral sliding mode surface; and controlling the multi-agent system model to reach an integral sliding mode surface according to a distributed fixed time inclusion consistency protocol and a dynamic event triggering mechanism, then sliding on the integral sliding mode surface, and controlling the state of the multi-agent system model to realize inclusion consistency within fixed time. According to the invention, the energy consumption of the system and the updating frequency of the controller can be reduced, the service life of the system is prolonged, and under a new distributed fixed time inclusion consistency protocol, the system firstly reaches the sliding mode surface and then slides on the sliding mode surface, so that the inclusion consistency of the system state is finally realized within fixed time.

A wind power generation system preset time maximum power point tracking control method comprises the following steps: firstly, establishing a wind power generation system dynamic model containing parameter uncertainty and external disturbance, and meanwhile, constructing a preset time convergence integral sliding mode surface; the method has the core advantages that the convergence time can be directly set by controller parameters and is irrelevant to the initial state of the system; secondly, designing a preset time self-adaptive controller based on the rotating speed tracking error and the sliding mode surface, and enabling the rotating speed tracking error to be quickly converged in preset time; the upper bound of lumped uncertainty of the system is estimated online through a self-adaptive mechanism, unknown dynamic and external disturbance are compensated in a unified mode, and dependence on an accurate model and disturbance prior knowledge is not needed; and finally, strictly proving the preset time stability of the closed-loop system through a Lyapunov stability theory. The method has good dynamic response performance and predictable convergence behaviors, and the robustness and the power generation efficiency of the system are improved.

The present invention discloses an unmanned ship adaptive path tracking control method, device, equipment and medium. The method comprises: establishing a dynamic model of an unmanned ship without parameter requirements, determining dynamic characteristics according to a simplified dynamic model of the directional force of the propeller of the unmanned ship, wherein the dynamic characteristics include unmodeled dynamic characteristics; fitting dynamic characteristics to the unmodeled dynamic characteristics through an RBF neural network; determining an integral sliding surface by using a preset construction method to determine the integral sliding surface by using a swell velocity error and a bow roll angle error; adaptively calculating the integral sliding surface to determine an adaptive rate, adaptively updating the fitted dynamic characteristics according to the adaptive rate, and obtaining real-time fitted dynamic characteristics; determining a real-time target thrust according to real-time swell and bow roll direction speeds and real-time fitted dynamic characteristics, and controlling the propeller motor according to the target thrust. The problem of being unable to effectively track and control the adaptive path of an unmanned ship can be solved by implementing the method of the present invention.

The invention belongs to the related technical field of robot control, and discloses a generalized impedance index integral sliding mode control method and device for a hexapod robot. The method comprises the steps that a hexapod robot leg joint space dynamic model is established and mapped to a Cartesian space, and modeling uncertainty and disturbance influence are considered; constructing a generalized impedance model fusing inertia, damping, rigidity and contact force tracking error weight; and defining an auxiliary variable based on the impedance error, designing an exponential global nonlinear integral sliding mode surface and a novel reaching law, and forming a controller. The device comprises a trajectory planner, a kinematics resolving module, a control decision module and other core components, and multi-module cooperation is achieved through inverse dynamic solution and a driver interface. According to the invention, the sliding mode control and the impedance model are integrated, so that accurate tracking control of the foot end contact force and position of the hexapod imported fire ant robot can be realized under the condition that modeling uncertainty and disturbance exist.

The invention discloses a sliding mode observation method for load torque of a permanent magnet synchronous motor. The load torque is observed according to the rotor angular velocity and the q-axis current to obtain the load torque observation value. The load torque observation value output by the load torque observer is sent to the sliding mode speed controller. The sliding mode speed controller adopts an integral sliding mode control mode to compensate the load torque in a manner that the load torque given value includes the load torque observation value item. The load torque observer adjusts the feedback gain according to the change of the load torque given value. When the system speed changes, or the parameters change, the load is disturbed, resulting in the load torque given value changing or / and the load torque observation value changing, the observation error of the load torque can be quickly reduced and the load torque compensation can be realized, thereby effectively weakening the jitter of the system, and the dynamic response speed is fast, the robustness is high, and the control accuracy of the motor speed is improved.

The invention discloses an unmanned ship distributed docking control system and method based on an integral sliding mode strategy, and the system comprises a positioning data obtaining module, an instruction issuing and processing module, an unmanned ship execution module, and an unmanned ship data feedback module. A dynamic communication topology network with environmental adaptability is constructed, anti-interference distributed information distribution is realized through a relay node dynamic distribution mechanism, and the problem of single-point failure of traditional centralized control is solved. Meanwhile, an error integral item is introduced into sliding mode surface design, and the buffeting phenomenon can be effectively reduced through the provided integral sliding mode control strategy. By disassembling the docking task, the expected longitude and latitude information of each member can be calculated respectively, and the expected longitude and latitude information is set as the position information under the follow coordinate system through coordinate conversion, so that the communication resources of the system can be saved to a great extent.

The present invention provides an offshore wind power control system based on disturbance observation and global fast integral sliding mode, including an offshore wind turbine, a doubly-fed induction generator, an optimal angular velocity tracking module, and a global fast integral sliding mode control module; the offshore wind turbine is used to convert the captured offshore wind energy into mechanical energy; the doubly-fed induction generator is used to convert mechanical energy into electrical energy; the maximum power point tracking module is used to calculate the variant power coefficient curve at the current moment considering unknown errors; based on the variant power coefficient curve, a disturbance tracking strategy is adopted to calculate the optimal angular velocity; the global fast integral sliding mode control module is used to control the current by adopting a PI control strategy. In the outer loop controller, a sliding mode surface function is set and a global fast control law is adopted for control to quickly adjust to the optimal angular velocity.

The application discloses a TBM cutter head main drive intelligent decision method and system, and belongs to the technical field of cutter head drive control. By constructing a master-slave type multi-drive unit collaborative architecture, unified regulation and control and target torque distribution of the drive system are realized; by monitoring current signals to identify faults, voltage vectors are reconstructed according to fault types, and continuous and stable output under faults is ensured; a disturbance observation method based on integral sliding mode is proposed, control deviation caused by system disturbance and parameter change is dynamically estimated and compensated; an MPTA control strategy of high-frequency virtual signal injection is designed, utilization of reluctance torque and stable tracking of the MTPA operating point are realized; the torque output capacity of the fault unit and the torque margin of the healthy unit are considered as a whole, a load distribution strategy is planned, and the overall load carrying capacity and operating life of the drive system are improved.

This invention relates to an AUV close-range docking method based on sliding mode adaptive control under ocean current interference. The controller design eliminates decoupling of the AUV's motion and incorporates an integral term in the sliding mode adaptive controller design, employing Integral Sliding Mode Adaptive Control (ISMAC) to minimize chattering during the AUV's approach motion. Finally, in designing the control parameters, overshoot is minimized at the expense of settling time to ensure successful docking. Furthermore, the estimation of ocean current velocity gives the system a certain degree of anti-interference capability, demonstrating its robustness.

The application discloses a permanent magnet synchronous motor speed and current model-free control method based on an improved second-order hyperlocal model, collects three-phase currents of the permanent magnet synchronous motor, constructs a second-order sliding mode observer on a mechanical angular velocity and total disturbance of the system based on an improved second-order hyperlocal model model-free sliding mode speed controller MFSMSC, observes the mechanical angular velocity and the total disturbance of the system, designs an adaptive approach law of a variable boundary layer and a second-order integral sliding mode surface, and obtains a q-axis current reference signal; the q-axis current reference signal is output to a model-free predictive current controller MFPCC based on the improved second-order hyperlocal model, dq-axis reference voltages are obtained, after inverse Park conversion, alpha-beta-axis stator voltage reference vectors are obtained, three-phase inverter switching driving signals are obtained through SVPWM operation, six switching tubes of the three-phase inverter are driven to be turned on and turned off, and then the three-phase winding currents of the permanent magnet synchronous motor are adjusted. The application adopts a classical cascade control architecture with a speed loop outer loop and a current loop inner loop, the improved second-order hyperlocal model improves disturbance estimation accuracy, and the improved second-order hyperlocal model enhances the suppression performance on high-frequency noise, and the MFPCC based on the improved second-order hyperlocal model improves the robustness of the system to motor parameter perturbation.